Method of calculating the odds of a sports play using data fidelity

ABSTRACT

A method of calculating the odds of a sports play using data fidelity by using a historical database and extracting the most recent play data and the previous play data, and comparing the extracted play to a set of rules to determine if the data is accurate and should be used to calculate wagering odds or if the data is inaccurate or contains an error which prompts action by the system, such as suspending the current wager market until the data that is received is accurate. Also, the method provides a method of calculating the odds of a sports play using data fidelity by using a historical database and extracting the most recent wager market data or wager odds data and the previous wager market data or wager odd data and compares the data to a set of rules to determine if the data is accurate.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present patent application is a continuation of U.S. applicationSer. No. 17/406,423, filed Aug. 19, 2021, which claims benefit andpriority to U.S. Provisional Patent Application No. 63/117,014, filed onNov. 23, 2020. The entire contents of each of the above-identifiedapplications are incorporated herein reference.

FIELD

The present embodiments are generally related to play-by-play wageringon live sporting events.

BACKGROUND

An issue with wagering platforms and wagering applications is that thedata in which the wager odds are calculated is often inaccurate.

Also, there are times when the live event data used to calculatewagering odds is incorrect or erroneous leading to inappropriate wagermarkets or odds that do not properly relate to the upcoming play.

Lastly, suppose a wagering platform or application receives incorrect orerroneous data. This can cause the wager markets that are based on thewagering platform or application to suffer unexpected losses or profits,leading to decreased user engagement and a lack of trust with theplatform or application.

Thus, there is a need in the prior art to have a method to determine thecredibility of the data received and the appropriate wager markets andodds.

SUMMARY

Methods, systems, and apparatuses for calculating odds of a sports playusing data fidelity may be shown and described. In one embodiment, amethod of ensuring accuracy of calculated odds on a sports wageringnetwork can include filtering at least one database for live event data;extracting recent and historical play data and/or odds data from atleast one database storing at least recent and historical play dataand/or odds data; determining differences in recent and historical playand/or odds data through comparison; utilizing differences in the recentand historical play and/or odds data to initiate extraction of at leastone play or system rule from a database governing the differences;executing a rule to suspend or disallow wager market activity on asports wagering network and/or to notify an administrator; storing rulesin at least one database; and displaying at least one message to anadministrator.

In another embodiment, a system for ensuring accuracy of calculated oddson a sports wagering network can include a base module configured toinitiate at least one play accuracy module and system accuracy module; aplay accuracy module configured to regulate odds based on changes inlive event play data by determining differences in stored data viacomparison and utilizing those differences to initiate extraction andexecution of at least one stored rule; a system accuracy moduleconfigured to regulate odds based on changes in wager profit data bydetermining differences in stored data via comparison and utilizingthose differences to initiate extraction and execution of at least onestored rule; a play rules database configured to store play rule data; asystem rules database configured to store system rule data; and a deviceconfigured to display a message.

BRIEF DESCRIPTIONS OF THE DRAWINGS

The accompanying drawings illustrate various embodiments of systems,methods, and various other aspects of the embodiments. Any person withordinary skill in the art will appreciate that the illustrated elementboundaries (e.g., boxes, groups of boxes, or other shapes) in thefigures represent an example of the boundaries. It may be understoodthat, in some examples, one element may be designed as multiple elementsor that multiple elements may be designed as one element. In someexamples, an element shown as an internal component of one element maybe implemented as an external component in another and vice versa.Furthermore, elements may not be drawn to scale. Non-limiting andnon-exhaustive descriptions are described with reference to thefollowing drawings. The components in the figures are not necessarily toscale, emphasis instead being placed upon illustrating principles.

FIG. 1 : illustrates a system for calculating the odds of a sports playusing data fidelity, according to an embodiment.

FIG. 2 : illustrates a base module, according to an embodiment.

FIG. 3 : illustrates a play accuracy module, according to an embodiment.

FIG. 4 : illustrates a system accuracy module, according to anembodiment.

FIG. 5 : illustrates a play rules database, according to an embodiment.

FIG. 6 : illustrates a system rules database, according to anembodiment.

DETAILED DESCRIPTION

Aspects of the present invention are disclosed in the followingdescription and related figures directed to specific embodiments of theinvention. Those of ordinary skill in the art will recognize thatalternate embodiments may be devised without departing from the spiritor the scope of the claims. Additionally, well-known elements ofexemplary embodiments of the invention will not be described in detailor will be omitted so as not to obscure the relevant details of theinvention

As used herein, the word exemplary means serving as an example, instanceor illustration. The embodiments described herein are not limiting, butrather are exemplary only. The described embodiments are not necessarilyto be construed as preferred or advantageous over other embodiments.Moreover, the terms embodiments of the invention, embodiments, orinvention do not require that all embodiments of the invention includethe discussed feature, advantage, or mode of operation.

Further, many of the embodiments described herein are described in termsof sequences of actions to be performed by, for example, elements of acomputing device. It should be recognized by those skilled in the artthat specific circuits can perform the various sequence of actionsdescribed herein (e.g., application specific integrated circuits(ASICs)) and/or by program instructions executed by at least oneprocessor. Additionally, the sequence of actions described herein can beembodied entirely within any form of computer-readable storage mediumsuch that execution of the sequence of actions enables the processor toperform the functionality described herein. Thus, the various aspects ofthe present invention may be embodied in several different forms, all ofwhich have been contemplated to be within the scope of the claimedsubject matter. In addition, for each of the embodiments describedherein, the corresponding form of any such embodiments may be describedherein as, for example, a computer configured to perform the describedaction.

With respect to the embodiments, a summary of the terminology usedherein is provided.

An action refers to a specific play or specific movement in a sportingevent. For example, an action may determine which players were involvedduring a sporting event. In some embodiments, an action may be a throw,shot, pass, swing, kick, and/or hit performed by a participant in asporting event. In some embodiments, an action may be a strategicdecision made by a participant in the sporting event, such as a player,coach, management, etc. In some embodiments, an action may be a penalty,foul, or other type of infraction occurring in a sporting event. In someembodiments, an action may include the participants of the sportingevent. In some embodiments, an action may include beginning events ofsporting event, for example opening tips, coin flips, opening pitch,national anthem singers, etc. In some embodiments, a sporting event maybe football, hockey, basketball, baseball, golf, tennis, soccer,cricket, rugby, MMA, boxing, swimming, skiing, snowboarding, horseracing, car racing, boat racing, cycling, wrestling, Olympic sport,eSports, etc. Actions can be integrated into the embodiments in avariety of manners.

A “bet” or “wager” is to risk something, usually a sum of money, againstsomeone else's or an entity based on the outcome of a future event, suchas the results of a game or event. It may be understood thatnon-monetary items may be the subject of a “bet” or “wager” as well,such as points or anything else that can be quantified for a “bet” or“wager.” A bettor refers to a person who bets or wagers. A bettor mayalso be referred to as a user, client, or participant throughout thepresent invention. A “bet” or “wager” could be made for obtaining orrisking a coupon or some enhancements to the sporting event, such asbetter seats, VIP treatment, etc. A “bet” or “wager” can be made forcertain amount or for a future time. A “bet” or “wager” can be made forbeing able to answer a question correctly. A “bet” or “wager” can bemade within a certain period. A “bet” or “wager” can be integrated intothe embodiments in a variety of manners.

A “book” or “sportsbook” refers to a physical establishment that acceptsbets on the outcome of sporting events. A “book” or “sportsbook” systemenables a human working with a computer to interact, according to set ofboth implicit and explicit rules, in an electronically powered domain toplace bets on the outcome of sporting event. An added game refers to anevent not part of the typical menu of wagering offerings, often postedas an accommodation to patrons. A “book” or “sportsbook” can beintegrated into the embodiments in a variety of manners.

To “buy points” means a player pays an additional price (more money) toreceive a half-point or more in the player's favor on a point spreadgame. Buying points means you can move a point spread, for example, upto two points in your favor. “Buy points” can be integrated into theembodiments in a variety of manners.

The “price” refers to the odds or point spread of an event. To “take theprice” means betting the underdog and receiving its advantage in thepoint spread. “Price” can be integrated into the embodiments in avariety of manners.

“No action” means a wager in which no money is lost or won, and theoriginal bet amount is refunded. “No action” can be integrated into theembodiments in a variety of manners.

The “sides” are the two teams or individuals participating in an event:the underdog and the favorite. The term “favorite” refers to the teamconsidered most likely to win an event or game. The “chalk” refers to afavorite, usually a heavy favorite. Bettors who like to bet bigfavorites are referred to “chalk eaters” (often a derogatory term). Anevent or game in which the sportsbook has reduced its betting limits,usually because of weather or the uncertain status of injured players,is referred to as a “circled game.” “Laying the points or price” meansbetting the favorite by giving up points. The term “dog” or “underdog”refers to the team perceived to be most likely to lose an event or game.A “longshot” also refers to a team perceived to be unlikely to win anevent or game. “Sides,” “favorite,” “chalk,” “circled game,” “laying thepoints price,” “dog,” and “underdog” can be integrated into theembodiments in a variety of manners.

The “money line” refers to the odds expressed in terms of money. Withmoney odds, whenever there is a minus (−), the player “lays” or is“laying” that amount to win (for example, $100); where there is a plus(+), the player wins that amount for every $100 wagered. A “straightbet” refers to an individual wager on a game or event that will bedetermined by a point spread or money line. The term “straight-up” meanswinning the game without any regard to the “point spread,” a“money-line” bet. “Money line,” “straight bet,” and “straight-up” can beintegrated into the embodiments in a variety of manners.

The “line” refers to the current odds or point spread on a particularevent or game. The “point spread” refers to the margin of points inwhich the favored team must win an event by to “cover the spread.” To“cover” means winning by more than the “point spread.” A handicap of the“point spread” value is given to the favorite team so bettors can choosesides at equal odds. “Cover the spread” means that a favorite wins anevent with the handicap considered or the underdog wins with additionalpoints. To “push” refers to when the event or game ends with no winneror loser for wagering purposes, a tie for wagering purposes. A “tie” isa wager in which no money is lost or won because the teams' scores wereequal to the number of points in the given “point spread.” The “openingline” means the earliest line posted for a particular sporting event orgame. The term “pick” or “pick 'em” refers to a game when neither teamis favored in an event or game. “Line,” “cover the spread,” “cover,”“tie,” “pick,” and “pick-em” can be integrated into the embodiments in avariety of manners.

To “middle” means to win both sides of a game; wagering on the“underdog” at one point spread and the favorite at a different pointspread and winning both sides. For example, if the player bets theunderdog +4½ and the favorite −3½ and the favorite wins by 4, the playerhas middled the book and won both bets. “Middle” can be integrated intothe embodiments in a variety of manners.

Digital gaming refers to any type of electronic environment that can becontrolled or manipulated by a human user for entertainment purposes. Asystem that enables a human and a computer to interact according to setof both implicit and explicit rules in an electronically powered domainfor the purpose of recreation or instruction. “eSports” refers to a formof sports competition using video games, or a multiplayer video gameplayed competitively for spectators, typically by professional gamers.Digital gaming and “eSports” can be integrated into the embodiments in avariety of manners.

The term event refers to a form of play, sport, contest, or game,especially one played according to rules and decided by skill, strength,or luck. In some embodiments, an event may be football, hockey,basketball, baseball, golf, tennis, soccer, cricket, rugby, MMA, boxing,swimming, skiing, snowboarding, horse racing, car racing, boat racing,cycling, wrestling, Olympic sport, etc. The event can be integrated intothe embodiments in a variety of manners.

The “total” is the combined number of runs, points or goals scored byboth teams during the game, including overtime. The “over” refers to asports bet in which the player wagers that the combined point total oftwo teams will be more than a specified total. The “under” refers tobets that the total points scored by two teams will be less than acertain figure. “Total,” “over,” and “under” can be integrated into theembodiments in a variety of manners.

A “parlay” is a single bet that links together two or more wagers; towin the bet, the player must win all the wagers in the “parlay.” If theplayer loses one wager, the player loses the entire bet. However, ifthey win all the wagers in the “parlay,” the player receives a higherpayoff than if the player had placed the bets separately. A “roundrobin” is a series of parlays. A “teaser” is a type of parlay in whichthe point spread, or total of each individual play is adjusted. Theprice of moving the point spread (teasing) is lower payoff odds onwinning wagers. “Parlay,” “round robin,” “teaser” can be integrated intothe embodiments in a variety of manners.

A “prop bet” or “proposition bet” means a bet that focuses on theoutcome of events within a given game. Props are often offered onmarquee games of great interest. These include Sunday and Monday nightpro football games, various high-profile college football games, majorcollege bowl games, and playoff and championship games. An example of aprop bet is “Which team will score the first touchdown?” “Prop bet” or“proposition bet” can be integrated into the embodiments in a variety ofmanners.

A “first-half bet” refers to a bet placed on the score in the first halfof the event only and only considers the first half of the game orevent. The process in which you go about placing this bet is the sameprocess that you would use to place a full game bet, but as previouslymentioned, only the first half is important to a first-half bet type ofwager. A “half-time bet” refers to a bet placed on scoring in the secondhalf of a game or event only. “First-half-bet” and “half-time-bet” canbe integrated into the embodiments in a variety of manners.

A “futures bet” or “future” refers to the odds that are posted well inadvance on the winner of major events. Typical future bets are the ProFootball Championship, Collegiate Football Championship, the ProBasketball Championship, the Collegiate Basketball Championship, and thePro Baseball Championship. “Futures bet” or “future” can be integratedinto the embodiments in a variety of manners.

The “listed pitchers” is specific to a baseball bet placed only if bothpitchers scheduled to start a game start. If they do not, the bet isdeemed “no action” and refunded. The “run line” in baseball refers to aspread used instead of the money line. “Listed pitchers,” “no action,”and “run line” can be integrated into the embodiments in a variety ofmanners.

The term “handle” refers to the total amount of bets taken. The term“hold” refers to the percentage the house wins. The term “juice” refersto the bookmaker's commission, most commonly the 11 to 10 bettors lay onstraight point spread wagers: also known as “vigorish” or “vig”. The“limit” refers to the maximum amount accepted by the house before theodds and/or point spread are changed. “Off the board” refers to a gamein which no bets are being accepted. “Handle,” “juice,” vigorish,”“vig,” and “off the board” can be integrated into the embodiments in avariety of manners.

“Casinos” are a public room or building where gambling games are played.“Racino” is a building complex or grounds having a racetrack andgambling facilities for playing slot machines, blackjack, roulette, etc.“Casino” and “Racino” can be integrated into the embodiments in avariety of manners.

Customers are companies, organizations or individuals that would deploy,for fees, and may be part of, or perform, various system elements ormethod steps in the embodiments.

Managed service user interface service is a service that can helpcustomers (1) manage third parties, (2) develop the web, (3) performdata analytics, (4) connect thru application program interfaces and (4)track and report on player behaviors. A managed service user interfacecan be integrated into the embodiments in a variety of manners.

Managed service risk management service are services that assistcustomers with (1) very important person management, (2) businessintelligence, and (3) reporting. These managed service risk managementservices can be integrated into the embodiments in a variety of manners.

Managed service compliance service is a service that helps customersmanage (1) integrity monitoring, (2) play safety, (3) responsiblegambling, and (4) customer service assistance. These managed servicecompliance services can be integrated into the embodiments in a varietyof manners.

Managed service pricing and trading service is a service that helpscustomers with (1) official data feeds, (2) data visualization, and (3)land based on property digital signage. These managed service pricingand trading services can be integrated into the embodiments in a varietyof manners.

Managed service and technology platforms are services that helpcustomers with (1) web hosting, (2) IT support, and (3) player accountplatform support. These managed service and technology platform servicescan be integrated into the embodiments in a variety of manners.

Managed service and marketing support services are services that helpcustomers (1) acquire and retain clients and users, (2) provide forbonusing options, and (3) develop press release content generation.These managed service and marketing support services can be integratedinto the embodiments in a variety of manners.

Payment processing services are services that help customers with (1)account auditing and (2) withdrawal processing to meet standards forspeed and accuracy. Further, these services can provide for integrationof global and local payment methods. These payment processing servicescan be integrated into the embodiments in a variety of manners.

Engaging promotions allow customers to treat players to free bets, oddsboosts, enhanced access, and flexible cashback to boost lifetime value.Engaging promotions can be integrated into the embodiments in a varietyof manners.

“Cash out” or “pay out” or “payout” allow customers to make available,on singles bets or accumulated bets with a partial cash out where eachoperator can control payouts by always managing commission andavailability. The “cash out” or “pay out” or “payout” can be integratedinto the embodiments in a variety of manners, including both monetaryand non-monetary payouts, such as points, prizes, promotional ordiscount codes, and the like.

“Customized betting” allows customers to have tailored personalizedbetting experiences with sophisticated tracking and analysis of players'behavior. “Customized betting” can be integrated into the embodiments ina variety of manners.

Kiosks are devices that offer interactions with customers, clients, andusers with a wide range of modular solutions for both retail and onlinesports gaming. Kiosks can be integrated into the embodiments in avariety of manners.

Business Applications are an integrated suite of tools for customers tomanage the everyday activities that drive sales, profit, and growth bycreating and delivering actionable insights on performance to helpcustomers to manage the sports gaming. Business Applications can beintegrated into the embodiments in a variety of manners.

State-based integration allows for a given sports gambling game to bemodified by states in the United States or other countries, based uponthe state the player is in, mobile phone, or other geolocationidentification means. State-based integration can be integrated into theembodiments in a variety of manners.

Game Configurator allows for configuration of customer operators to havethe opportunity to apply various chosen or newly created business ruleson the game as well as to parametrize risk management. The GameConfigurator can be integrated into the embodiments in a variety ofmanners.

“Fantasy sports connectors” are software connectors between method stepsor system elements in the embodiments that can integrate fantasy sports.Fantasy sports allow a competition in which participants selectimaginary teams from among the players in a league and score pointsaccording to the actual performance of their players. For example, if aplayer in fantasy sports is playing at a given real-time sport, oddscould be changed in the real-time sports for that player.

Software as a service (or SaaS) is a software delivery and licensingmethod in which software is accessed online via a subscription ratherthan bought and installed on individual computers. Software as a servicecan be integrated into the embodiments in a variety of manners.

Synchronization of screens means synchronizing bets and results betweendevices, such as TV and mobile, PC, and wearables. Synchronization ofscreens can be integrated into the embodiments in a variety of manners.

Automatic content recognition (ACR) is an identification technology thatrecognizes content played on a media device or present in a media file.Devices containing ACR support enable users to quickly obtain additionalinformation about the content they see without any user-based input orsearch efforts. A short media clip (audio, video, or both) is selectedto start the recognition. This clip could be selected from within amedia file or recorded by a device. Through algorithms such asfingerprinting, information from the actual perceptual content is takenand compared to a database of reference fingerprints, wherein eachreference fingerprint corresponds with a known recorded work. A databasemay contain metadata about the work and associated information,including complementary media. If the media clip's fingerprint ismatched, the identification software returns the corresponding metadatato the client application. For example, during an in-play sports game, a“fumble” could be recognized and at the time stamp of the event,metadata such as “fumble” could be displayed. Automatic contentrecognition (ACR) can be integrated into the embodiments in a variety ofmanners.

Joining social media means connecting an in-play sports game bet orresult to a social media connection, such as a FACEBOOK® chatinteraction. Joining social media can be integrated into the embodimentsin a variety of manners.

Augmented reality means a technology that superimposes acomputer-generated image on a user's view of the real world, thusproviding a composite view. In an example of this invention, a real timeview of the game can be seen and a “bet”—which is a computer-generateddata point—is placed above the player that is bet on. Augmented realitycan be integrated into the embodiments in a variety of manners.

Some embodiments of this disclosure, illustrating all its features, willnow be discussed in detail. It can be understood that the embodimentsare intended to be open-ended in that an item or items used in theembodiments is not meant to be an exhaustive listing of such item oritems or meant to be limited to only the listed item or items.

It can be noted that as used herein and in the appended claims, thesingular forms “a,” “an,” and “the” include plural references unless thecontext clearly dictates otherwise. Although any systems and methodssimilar or equivalent to those described herein can be used in thepractice or testing of embodiments, only some exemplary systems andmethods are now described.

FIG. 1 is a system for calculating the odds of a sports play using datafidelity. This system may include a live event 102, for example, asporting event such as a football, basketball, baseball, or hockey game,tennis match, golf tournament, eSports, or digital game, etc. The liveevent 102 may include some number of actions or plays, upon which auser, bettor, or customer can place a bet or wager, typically through anentity called a sportsbook. There are numerous types of wagers thebettor can make, including, but not limited to, a straight bet, a moneyline bet, or a bet with a point spread or line that the bettor's teamwould need to cover if the result of the game with the same as the pointspread the user would not cover the spread, but instead the tie iscalled a push. If the user bets on the favorite, points are given to theopposing side, which is the underdog or longshot. Betting on allfavorites is referred to as chalk and is typically applied toround-robin or other tournaments' styles. There are other types ofwagers, including, but not limited to, parlays, teasers, and prop bets,which are added games that often allow the user to customize theirbetting by changing the odds and payouts received on a wager. Certainsportsbooks will allow the bettor to buy points which moves the pointspread off the opening line. This increases the price of the bet,sometimes by increasing the juice, vig, or hold that the sportsbooktakes. Another type of wager the bettor can make is an over/under, inwhich the user bets over or under a total for the live event 102, suchas the score of an American football game or the run line in a baseballgame, or a series of actions in the live event 102. Sportsbooks haveseveral bets they can handle, limiting the number of wagers they cantake on either side of a bet before they will move the line or odds offthe opening line. Additionally, there are circumstances, such as aninjury to an important player like a listed pitcher, in which asportsbook, casino, or racino may take an available wager off the board.As the line moves, an opportunity may arise for a bettor to bet on bothsides at different point spreads to middle, and win, both bets.Sportsbooks will often offer bets on portions of games, such asfirst-half bets and half-time bets. Additionally, the sportsbook canoffer futures bets on live events in the future. Sportsbooks need tooffer payment processing services to cash out customers which can bedone at kiosks at the live event 102 or at another location.

Further, embodiments may include a plurality of sensors 104 that may beused such as motion, temperature, or humidity sensors, optical sensors,and cameras such as an RGB -D camera which is a digital camera capableof capturing color (RGB) and depth information for every pixel in animage, microphones, radiofrequency receivers, thermal imagers, radardevices, lidar devices, ultrasound devices, speakers, wearable devices,etc. Also, the plurality of sensors 104 may include but are not limitedto, tracking devices, such as RFID tags, GPS chips, or other suchdevices embedded on uniforms, in equipment, in the field of play andboundaries of the field of play, or on other markers in the field ofplay. Imaging devices may also be used as tracking devices, such asplayer tracking, which provide statistical information through real-timeX, Y positioning of players and X, Y, Z positioning of the ball.

Further, embodiments may include a cloud 106 or a communication networkthat may be a wired and/or wireless network. The communication network,if wireless, may be implemented using communication techniques such asvisible light communication (VLC), worldwide interoperability formicrowave access (WiMAX), long term evolution (LTE), wireless local areanetwork (WLAN), infrared (IR) communication, public switched telephonenetwork (PSTN), radio waves, or other communication techniques that areknown in the art. The communication network may allow ubiquitous accessto shared pools of configurable system resources and higher-levelservices that can be rapidly provisioned with minimal management effort,often over the internet, and relies on sharing resources to achievecoherence and economies of scale, like a public utility. In contrast,third-party clouds allow organizations to focus on their core businessesinstead of expending resources on computer infrastructure andmaintenance. The cloud 106 may be communicatively coupled to apeer-to-peer wagering network 114, which may perform real-time analysison the type of play and the result of the play. The cloud 106 may alsobe synchronized with game situational data such as the time of the game,the score, location on the field, weather conditions, and the like,which may affect the choice of play utilized. For example, in anexemplary embodiment, the cloud 106 may not receive data gathered fromthe sensors 104 and may, instead, receive data from an alternative datafeed, such as Sports Radar®. This data may be compiled substantiallyimmediately following the completion of any play and may be comparedwith a variety of team data and league data based on a variety ofelements, including the current down, possession, score, time, team, andso forth, as described in various exemplary embodiments herein.

Further, embodiments may include a mobile device 108 such as a computingdevice, laptop, smartphone, tablet, computer, smart speaker, or I/Odevices. I/O devices may be present in the computing device. Inputdevices may include but are not limited to, keyboards, mice, trackpads,trackballs, touchpads, touch mice, multi-touch touchpads and touch mice,microphones, multi-array microphones, drawing tablets, cameras,single-lens reflex cameras (SLRs), digital SLRs (DSLRs), complementarymetal-oxide semiconductor (CMOS) sensors, accelerometers, IR opticalsensors, pressure sensors, magnetometer sensors, angular rate sensors,depth sensors, proximity sensors, ambient light sensors, gyroscopicsensors, or other sensors. Output devices may include but are notlimited to, video displays, graphical displays, speakers, headphones,inkjet printers, laser printers, or 3D printers. Devices may include,but are not limited to, a combination of multiple input or outputdevices such as, Microsoft KINECT, Nintendo Wii remote, Nintendo WII UGAMEPAD, or Apple iPhone. Some devices allow gesture recognition inputsby combining input and output devices. Other devices allow for facialrecognition, which may be utilized as an input for different purposessuch as authentication or other commands. Some devices provide for voicerecognition and inputs including, but not limited to, Microsoft KINECT,SIRI for iPhone by Apple, Google Now, or Google Voice Search. Additionaluser devices have both input and output capabilities including but notlimited to, haptic feedback devices, touchscreen displays, ormulti-touch displays. Touchscreen, multi-touch displays, touchpads,touch mice, or other touch sensing devices may use differenttechnologies to sense touch, including but not limited to, capacitive,surface capacitive, projected capacitive touch (PCT), in-cellcapacitive, resistive, IR, waveguide, dispersive signal touch (DST),in-cell optical, surface acoustic wave (SAW), bending wave touch (BWT),or force-based sensing technologies. Some multi-touch devices may allowtwo or more contact points with the surface, allowing advancedfunctionality including, but not limited to, pinch, spread, rotate,scroll, or other gestures. Some touchscreen devices, including but notlimited to, Microsoft PIXELSENSE or Multi-Touch Collaboration Wall, mayhave larger surfaces, such as on a table-top or on a wall, and may alsointeract with other electronic devices. Some I/O devices, displaydevices, or groups of devices may be augmented reality devices. An I/Ocontroller may control one or more I/O devices, such as a keyboard and apointing device, or a mouse or optical pen. Furthermore, an I/O devicemay also contain storage and/or an installation medium for the computingdevice. In some embodiments, the computing device may include USBconnections (not shown) to receive handheld USB storage devices. Infurther embodiments, an I/O device may be a bridge between the systembus and an external communication bus, e.g., USB, SCSI, FireWire,Ethernet, Gigabit Ethernet, Fiber Channel, or Thunderbolt buses. In someembodiments, the mobile device 108 could be an optional component andwould be utilized in a situation where a paired wearable device employsthe mobile device 108 for additional memory or computing power orconnection to the internet.

Further, embodiments may include a wagering software application or awagering app 110, which is a program that enables the user to place betson individual plays in the live event 102, streams audio and video fromthe live event 102, and features the available wagers from the liveevent 102 on the mobile device 108. The wagering app 110 allows the userto interact with the wagering network 114 to place bets and providepayment/receive funds based on wager outcomes.

Further, embodiments may include a mobile device database 112 that maystore some or all the user's data, the live event 102, or the user'sinteraction with the wagering network 114.

Further, embodiments may include the wagering network 114, which mayperform real-time analysis on the type of play and the result of a playor action. The wagering network 114 (or the cloud 106) may also besynchronized with game situational data, such as the time of the game,the score, location on the field, weather conditions, and the like,which may affect the choice of play utilized. For example, in anexemplary embodiment, the wagering network 114 may not receive datagathered from the sensors 104 and may, instead, receive data from analternative data feed, such as SportsRadar®. This data may be providedsubstantially immediately following the completion of any play and maybe compared with a variety of team data and league data based on avariety of elements, including the current down, possession, score,time, team, and so forth, as described in various exemplary embodimentsherein. The wagering network 114 can offer several SaaS managed servicessuch as user interface service, risk management service, compliance,pricing and trading service, IT support of the technology platform,business applications, game configuration, state-based integration,fantasy sports connection, integration to allow the joining of socialmedia, or marketing support services that can deliver engagingpromotions to the user.

Further, embodiments may include a user database 116, which may containdata relevant to all users of the wagering network 114 and may include,but is not limited to, a user ID, a device identifier, a paired deviceidentifier, wagering history, or wallet information for the user. Theuser database 116 may also contain a list of user account recordsassociated with respective user IDs. For example, a user account recordmay include, but is not limited to, information such as user interests,user personal details such as age, mobile number, etc., previouslyplayed sporting events, highest wager, favorite sporting event, orcurrent user balance and standings. In addition, the user database 116may contain betting lines and search queries. The user database 116 maybe searched based on a search criterion received from the user. Eachbetting line may include but is not limited to, a plurality of bettingattributes such as at least one of the following: the live event 102, ateam, a player, an amount of wager, etc. The user database 116 mayinclude, but is not limited to, information related to all the usersinvolved in the live event 102. In one exemplary embodiment, the userdatabase 116 may include information for generating a user authenticityreport and a wagering verification report. Further, the user database116 may be used to store user statistics like, but not limited to, theretention period for a particular user, frequency of wagers placed by aparticular user, the average amount of wager placed by each user, etc.

Further, embodiments may include a historical plays database 118 thatmay contain play data for the type of sport being played in the liveevent 102. For example, in American Football, for optimal oddscalculation, the historical play data may include data or metadata aboutthe live event and/or historical plays, such as time, location, weather,previous plays, scores, winners, losers, opponent data, physiologicaldata, team record data, etc. Further, embodiments may utilize an oddsdatabase 120—that contains the odds calculated by an odds calculationmodule 122—to display the odds on the user's mobile device 108 and takebets from the user through the mobile device wagering app 110.

Further, embodiments may include the odds calculation module 122, whichutilizes historical play data to calculate odds for in-play wagers.

Further, embodiments may include a base module 124, which may begin withthe base module 124 initiating the play accuracy module 126. Forexample, the play accuracy module 126 may filter the historical playsdatabase 118 for the live event 102. The play accuracy module 126 mayquery the historical plays database 118 for the most recent play orentry. The play accuracy module 126 may extract the play data from thehistorical play database 118. The play accuracy module 126 may query thehistorical plays database 118 for the previous play data. The playaccuracy module 126 may extract the previous play data from thehistorical plays database 118. The play accuracy module 126 may comparethe extracted play data with the play rules database 130. The playaccuracy module 126 may determine if a match exists between theextracted play data and the rules stored in the play rules database 130.If there is a match, the play accuracy module 126 may extract thecorresponding rule from the play rules database 130. The play accuracymodule 126 may execute the extracted rule from the play rules database130. If there is no match or after the extracted rule is executed, theplay accuracy module 126 may return to the base module 124. The basemodule 124 may initiate the system accuracy module 128. The systemaccuracy module 128 may filter the odds database 120 for the live event102. The system accuracy module 128 may query the odds database 120 forthe most recent wager market or odds. The system accuracy module 128 mayextract the wager market data from the odds database 120. The systemaccuracy module 128 may query the odds database 120 for the previouswager market data. The system accuracy module 128 may extract theprevious wager market data from the odds database 120. The systemaccuracy module 128 may compare the extracted wager market data with thesystem rules database 132. The system accuracy module 128 may determineif there is a match between the extracted wager market data and therules stored in the system rules database 132. If there is a match, thesystem accuracy module 128 may extract the corresponding rule from thesystem rules database 132. The system accuracy module 128 may executethe extracted rule from the system rules database 132. If there is nomatch or after the extracted rule is executed, the system accuracymodule 128 may return to the base module 124.

Further, embodiments may include a play accuracy module 126, which maybegin with the base module 124 initiating the play accuracy module 126.The play accuracy module 126 may filter the historical plays database118 for the live event 102. For example, if the live event 102 is theBoston Red Sox vs. the New York Yankees, the historical plays database118 may be filtered for all historical plays for the Boston Red Sox vs.the New York Yankees. The play accuracy module 126 may query thehistorical plays database 118 for the most recent play or entry. Forexample, the most recent play may be in the Boston Red Sox vs. the NewYork Yankees event in the bottom of the second inning, with the numberthree batter up at the plate, such as J. D. Martinez, with one out andno runners on base, and five pitches have been thrown. The play accuracymodule 126 may extract the play data from the historical play database118. For example, the extracted play data may be the Boston Red Sox vs.the New York Yankees event in the bottom of the second inning, with thenumber three batter up at the plate, such as J. D. Martinez, with oneout and no runners on base, and five pitches have been thrown. The playaccuracy module 126 may query the historical plays database 118 for theprevious play data. For example, the play accuracy module 126 may querythe historical plays database 118 for the second most recent play, thesecond newest entry in the historical plays database 118, or the dataentry previously entered before the most recent play. The play accuracymodule 126 may extract the previous play data from the historical playsdatabase 118. For example, the data extracted may be the Boston Red Soxvs. the New York Yankees event in the bottom of the second inning, withthe number three batter up at the plate, such as J. D. Martinez, withone out and no runners on base, and three pitches have been thrown. Theplay accuracy module 126 may compare the extracted play data to the playrules database 130. For example, the play accuracy module 126 maycompare the extracted play data to the play rules database 130 todetermine the differences between the two data entries, such as thenumber of pitches increased since the most recent entry. The playaccuracy module 126 may determine if there is an associated rule withthe difference in data. Another example may be if the inning from themost recent data entry was the bottom of the fourth inning and thesecond most recent data entry has the live event 102 in the top of thesecond inning, meaning an increase of two innings. The play accuracymodule 126 may determine if there is a match between the extracted playdata and the rules stored in the play rules database 130. For example,if the number of pitches increased by two since the previous data entry,there may be a match with the data stored in the play rules database130, thereby causing the corresponding action to be extracted andexecuted. Similarly, if the innings increased by two, there may also bea match to the data stored in the play rules database 130, therebycausing the corresponding action to be extracted and executed. If thereis a match, the play accuracy module 126 may extract the correspondingrule from the play rules database 130. For example, if the number ofpitches increased by two from the previous data entry and the mostrecent data entry, there may be a match, and the corresponding actionmay be to suspend the wagering market. For example, the wagering marketmay not offer wager odds to the user until there are no matches betweenthe differences in the two data entries and play rules database 130thereby ensuring that the data received by the wagering network 114 iscorrect and without error. The play accuracy module 126 may execute theextracted rule from the play rules database 130. For example, thecorresponding rule or corresponding action may be to suspend thewagering market. In another example, the wagering market may not offerwager odds to the user until there were no matches between thedifferences in the two data entries and play rules database 130 therebyensuring that the data being received by the wagering network 114 iscorrect and without error. If there is no match or after the extractedrule is executed, the play accuracy module 126 may return to the basemodule 124.

Further, embodiments may include a system accuracy module 128, which maybegin with the base module 124 initiating the system accuracy module128. The system accuracy module 128 may filter the odds database 120 forthe live event 102. For example, the system accuracy module 128 mayfilter the odds database 120 for the live event 102 of the Boston RedSox vs. the New York Yankees. The system accuracy module 128 may querythe odds database 120 for the most recent wager market or odds. Forexample, the system accuracy module 128 may query the odds database 120for the most recent wager market or odds offered for the live event 102,such as the in the second inning of the Boston Red Sox vs. the New YorkYankees event with J. D. Martinez at-bat, the fifth pitch was a ball,resulting in the house or the wagering network 114 collecting $10,000.The system accuracy module 128 may extract the wager market data fromthe odds database 120. For example, the data extracted may be in thesecond inning in the Boston Red Sox vs. the New York Yankees event withJ. D. Martinez at-bat, wherein the fifth pitch was a ball that resultedin the wagering network 114 collecting $10,000. The system accuracymodule 128 may query the odds database 120 for the previous wager marketdata. For example, the system accuracy module 128 may query the oddsdatabase 120 for the wager odds data for the wagering market before themost recent wager market or the second most recent data entry in theodds database 120. For example, the data may be in the second inning inthe Boston Red Sox vs. the New York Yankees event with J. D. Martinezat-bat, wherein the fourth pitch was a ball, resulting in the house orthe wagering network 114 collecting $50,000. The system accuracy module128 may extract the previous wager market data from the odds database120. For example, the data extracted may be in the second inning in theBoston Red Sox vs. the New York Yankees event with J. D. Martinezat-bat, wherein the fourth pitch was a ball, resulting in the wageringnetwork 114 collecting $50,000. The system accuracy module 128 maycompare the extracted wager market data to the system rules database132. For example, the system accuracy module 128 may compare the twoextracted data entries in which the difference is on the fourth pitchwhere the house or wagering network 114 collected $50,000, and on thefifth pitch, where the house collected $10,000 on the wagers for thepitch to be a ball, which may be a decrease of 80% in collections orprofits for the house. The system accuracy module 128 may determine ifthere is a match between the extracted wager market data and the rulesstored in the system rules database 132. For example, the differencebetween the two data entries may be that the house profits decreased by80%, so there may be a match between the two data entries and the datastored in the system rules database 132, which may result in thecorresponding action to be extracted and executed. If there is a match,the system accuracy module 128 may extract the corresponding rule fromthe system rules database 132. For example, the difference between thetwo data entries may be that the house profits decreased by 80%, sothere may be a match between the two data entries and the data stored inthe system rules database 132, which may result in the correspondingaction, such as the wagering market being suspended, or a systemadministrator being notified. The decrease in profits for the house orwagering network 114 may be because of incorrect or erroneous datareceived by the wagering network 114 to create the odds, therebypotentially resulting in inappropriate or incorrect wager odds thateither make the house lose profits drastically or allow the house tocollect profits drastically; this may in turn lower user engagement dueto a lack of trust in the system. The system accuracy module 128 mayexecute the extracted rule from the system rules database 132. Forexample, the corresponding action may be to suspend the wagering marketor notify an administrator to correct the wager odds or check the systemto ensure that the data being received from the live event 102 iscorrect and without errors thereby potentially preventing furtherdrastically increased or decreased profits for the wagering network 114.If there is no match or after the extracted rule is executed, the systemaccuracy module 128 may return to the base module 124.

Further, embodiments may include a play rules database 130. The playrules database 130 may contain the rule ID, such as Base12354, the eventtype, such as baseball, the rule, such as if the pitch number increasesby two, and the action, such as suspend the wagering market. The playrules database 130 may be used in the process described in the playaccuracy module 126, wherein the two most recent plays from a live event102 are extracted from the historical plays database 118 and compared tothe play rules database 130 to determine if the two extracted dataentries match any of the rules listed and if so, execute thecorresponding action. This comparison may prevent the wagering network114 from using erroneous data from the live event 102, which may lead tothe creation of inappropriate or wrong wagering odds or wagering oddsthat do not fully represent the current state of the live event 102. Insome embodiments, the play rules database 130 may contain data formultiple sports or events such as baseball, football, soccer, hockey,tennis, golf, etc. In some embodiments, the play rules database 130 maycontain other rules or actions that limit or suspend wager markets untilthe data being received is deemed correct, or if there is a continuousstream of incorrect data, then the play rules database 130 may containan action to inform or notify a system administrator to correct the databeing received or perform some other action to correctly create wageringodds for the live event 102.

Further, embodiments may include a system rules database 132. The systemrules database 132 may contain the rule ID, such as Sys45632, the rule,such as if wager profits decrease by 80%, and the action, such assuspend the wagering market and notify a system administrator. Thesystem rules database 132 may be used in the process described in thesystem accuracy module 128, wherein which the two most wager markets forthe live event 102 are extracted from the odds database 120 and comparedto the system rules database 132 to determine if the two extracted dataentries match any of the rules listed and if so, execute thecorresponding action. This comparison may prevent the wagering network114 from using data from the live event 102 that may be erroneous,leading to the creation of inappropriate or wrong wagering odds orwagering odds that do not fully represent the current state of the liveevent 102. The system rules database 132 may contain rules based onpotential system errors that may be caused by receiving incorrect orerror-filled data from the live event 102 that may potentially have adrastic outcome on the profits or losses for the wagering network 114.This may lead the wagering network 114 to incorrectly losing large sumsof profits or gaining profits incorrectly, thereby potentially leadingto mistrust with users and loss of user engagement. In some embodiments,the system rules database 132 may contain other rules or actions thatlimit or suspend wagering markets until the data being received isdeemed correct. If there is a continuous stream of incorrect data, thesystem rules database 132 may contain an action to inform or notify asystem administrator to correct the data being received or perform someother action to correctly create wagering odds for the live event 102.

FIG. 2 illustrates the base module 124. The process may begin with thebase module 124 initiating, at step 200, the play accuracy module 126.The base module 124 may then initiate, at step 202, the system accuracymodule 128.

FIG. 3 illustrates the play accuracy module 126. The process may beginwith the base module 124 initiating, at step 300, the play accuracymodule 126. The play accuracy module 126 may filter, at step 302, thehistorical plays database 118 for the live event 102. For example, ifthe live event 102 is the Boston Red Sox vs. the New York Yankees, thehistorical plays database 118 may be filtered for all historical playsfor the Boston Red Sox vs. the New York Yankees. The play accuracymodule 126 may query, at step 304, the historical plays database 118 forthe most recent play or entry. For example, the most recent play may bein the Boston Red Sox vs. the New York Yankees event in the bottom ofthe second inning, with the number three batter up at the plate, such asJ. D. Martinez, with one out and no runners on base, and five pitcheshave been thrown. The play accuracy module 126 may extract, at step 306,the play data from the historical play database 118. For example, theextracted data may be the Boston Red Sox vs. the New York Yankees eventin the bottom of the second inning, with the number three batter up atthe plate, such as J. D. Martinez, with one out and no runners on base,and five pitches have been thrown. The play accuracy module 126 mayquery, at step 308, the historical plays database 118 for the previousplay data. For example, the play accuracy module 126 may query thehistorical plays database 118 for the second most recent play, thesecond newest entry in the historical plays database 118, or the dataentry previously entered before the most recent play. The play accuracymodule 126 may extract, at step 310, the previous play data from thehistorical plays database 118. For example, the extracted data may bethe Boston Red Sox vs. the New York Yankees event in the bottom of thesecond inning, with the number three batter up at the plate, such as J.D. Martinez, with one out and no runners on base, and three pitches havebeen thrown. The play accuracy module 126 may compare, at step 312, theextracted play data with the play rules database 130. For example, thecomparison may determine the differences between the two data entries,such the number of pitches has increased by two or that the most recententry has five pitches thrown and the previous entry from that has threepitches thrown. So, the two-pitch increase may be compared to the playrules database 130 to determine if there is an associated rule with thedifference in data. Another example may be that the inning from the mostrecent data entry was the bottom of the fourth inning and the secondmost recent data entry has the event in the top of the second inning,which may be an increase of two innings. The play accuracy module 126may determine, at step 314, if there is a match between the extractedplay data and the rules stored in the play rules database 130. Forexample, if the number of pitches increased by two from the previousdata entry and the most recent data entry, there may be a match to thedata stored in the play rules database 130, and the corresponding actionmay be extracted and executed. Similarly, if the innings increased bytwo, there may also be a match to the data stored in the play rulesdatabase 130, and the corresponding action may be extracted andexecuted. If there is a match, the play accuracy module 126 may extract,at step 316, the corresponding rule from the play rules database 130.For example, if the number of pitches increased by two from the previousdata entry and the most recent data entry, there may be a match, and thecorresponding action may be to suspend the wagering market. For example,the wagering market may not offer wager odds to the user until therewere no matches between the differences in the two data entries and playrules database 130 thereby ensuring that the data being received by thewagering network 114 is correct and without error. The play accuracymodule 126 may execute, at step 318, the extracted rule from the playrules database 130. For example, the corresponding rule or correspondingaction may be to suspend the wagering market. For example, the wageringmarket may not offer wager odds to the user until there were no matchesbetween the differences in the two data entries and play rules database130 to ensure that the data being received by the wagering network 114is correct and without error. If there is no match or after theextracted rule is executed, the play accuracy module 126 may return, atstep 320, to the base module 124.

FIG. 4 illustrates the system accuracy module 128. The process may beginwith the base module 124 initiating, at step 400, the system accuracymodule 128. The system accuracy module 128 may filter, at step 402, theodds database 120 for the live event 102. For example, the systemaccuracy module 128 may filter the odds database 120 for the live event102 of the Boston Red Sox vs. the New York Yankees. The system accuracymodule 128 may query, at step 404, the odds database 120 for the mostrecent wager market or wager odds. For example, the system accuracymodule 128 may query the odds database 120 for the most recent wagermarket, or the most recent odds offered on the live event 102, such asthe in the second inning in the Boston Red Sox vs. the New York Yankeesevent with J. D. Martinez at-bat the fifth pitch was a ball which mayresult in the house or the wagering network 114 collecting $10,000. Thesystem accuracy module 128 may extract, at step 406, the wager marketdata from the odds database 120. For example, the data extracted may bein the second inning in the Boston Red Sox vs. the New York Yankeesevent with J. D. Martinez at-bat, wherein the fifth pitch was a ball,resulting in the house or the wagering network 114 collecting $10,000.The system accuracy module 128 may query, at step 408, the odds database120 for the previous wager market data. For example, the system accuracymodule 128 may query the odds database 120 for the wager odds data forthe wagering market before the most recent wager market or the secondmost recent data entry in the odds database 120. For example, the datamay be in the second inning in the Boston Red Sox vs. the New YorkYankees event with J. D. Martinez at-bat the fourth pitch was a ballwhich may result in the house or the wagering network 114 collecting$50,000. The system accuracy module 128 may extract, at step 410, theprevious wager market data from the odds database 120. For example, thedata extracted may be in the second inning in the Boston Red Sox vs. theNew York Yankees event with J. D. Martinez at-bat the fourth pitch was aball that resulted in the house or the wagering network 114 collecting$50,000. The system accuracy module 128 may compare, at step 412, theextracted wager market data to the system rules database 132. Forexample, the system accuracy module 128 may compare the two extracteddata entries in which the difference is on the fourth pitch the house orwagering network 114 collected $50,000, and on the fifth pitch, thehouse collected $10,000 on the wagers for the pitch to be a ball, whichmay be a decrease of 80% in collections or profits for the house. Thesystem accuracy module 128 may determine, at step 414, if there is amatch between the extracted wager market data and the rules stored inthe system rules database 132. For example, the difference between thetwo data entries is that the house profits decreased by 80%, so theremay be a match between the two data entries and the data stored in thesystem rules database 132, which may result in the corresponding actionto be extracted and executed. If there is a match, the system accuracymodule 128 may extract, at step 416, the corresponding rule from thesystem rules database 132. For example, the difference between the twodata entries is the house profits decreased by 80%, so there may be amatch between the two data entries and the data stored in the systemrules database 132, which may result in the corresponding action, suchas the wagering market being suspended, and a system administrator beingnotified. The decrease in profits for the house or wagering network 114may be because the wagering network 114 received incorrect or erroneousdata used to create the odds thereby potentially resulting ininappropriate or incorrect wager odds that may either make the houselose profits drastically or allow the house to collect profitsdrastically which may lower user engagement due to a lack of trust inthe system. The system accuracy module 128 may execute, at step 418, theextracted rule from the system rules database 132. For example, thecorresponding action may be to suspend the wagering market and notify anadministrator to correct the wager odds or check the system to ensurethat the data being received from the live event 102 is correct and doesnot contain errors to prevent further drastically increased or decreasedprofits for the wagering network 114. If there is no match or after theextracted rule is executed, the system accuracy module 128 may return,at step 420, to the base module 124.

FIG. 5 illustrates the play rules database 130. The play rules database130 may contain the rule ID, such as Base12354, the event type, such asbaseball, the rule, such as if the pitch number increases by two, andthe action, such as suspend the wagering market. The play rules database130 may be used in the process described in the play accuracy module126, wherein the two most recent plays from the live event 102 areextracted from the historical plays database 118 and compared to theplay rules database 130 to determine if the two extracted data entriesmatch any of the rules listed and if so, execute the correspondingaction. This comparison may prevent the wagering network 114 from usingdata from the live event 102 that may be considered erroneous, leadingto the creation of inappropriate or wrong wagering odds or wagering oddsthat do not fully represent the current state of the live event 102. Insome embodiments, the play rules database 130 may contain data formultiple sports or events such as baseball, football, soccer, hockey,tennis, golf, etc. In some embodiments, the play rules database 130 maycontain other rules or actions that limit or suspend wagering markets(or otherwise govern or control the wagering markets) until the databeing received is deemed correct, or if there is a continuous stream ofincorrect data, then the play rules database 130 may contain an actionto inform or notify a system administrator to correct the data beingreceived or perform some other action to correctly create wagering oddsfor the live event 102.

FIG. 6 illustrates the system rules database 132. The system rulesdatabase 132 may contain the rule ID, such as Sys45632, the rule, suchas if wager profits decrease by 80%, and the action, such as suspend thewagering market and notify a system administrator, or other contain andexecute a series of governing or controlling rules or actions. Thesystem rules database 132 may be used in the process described in thesystem accuracy module 128, wherein the two most wager markets for thelive event 102 are extracted from the odds database 120 and compared tothe system rules database 132 to determine if the two extracted dataentries match any of the rules listed and if so, execute thecorresponding action. This comparison may prevent the wagering network114 from using data from the live event 102 that may be considerederroneous, leading to the creation of inappropriate or wrong wageringodds or wagering odds that do not fully represent the current state ofthe live event 102. The system rules database 132 may contain rulesbased on potential system errors that may be caused by receivingincorrect or error-filled data from the live event 102 that maypotentially have a drastic outcome on the profits or losses for thewagering network 114, which may lead to the wagering network 114incorrectly losing large sums of profits or gaining profits incorrectlywhich may lead to mistrust with users and lead to less user engagement.In some embodiments, the system rules database 132 may contain othercontrolling rules or actions that limit or suspend wagering marketsuntil the data being received is deemed correct, or if there is acontinuous stream of incorrect data, then the system rules database 132may contain an action to inform or notify a system administrator tocorrect the data being received or perform some other action tocorrectly create wagering odds for the live event 102.

The foregoing description and accompanying figures illustrate theprinciples, preferred embodiments, and modes of operation of theinvention. However, the invention should not be construed as beinglimited to the embodiments discussed above. Additional variations of theembodiments discussed above will be appreciated by those skilled in theart.

Therefore, the above-described embodiments should be regarded asillustrative rather than restrictive. Accordingly, it should beappreciated that variations to those embodiments can be made by thoseskilled in the art without departing from the scope of the invention asdefined by the following claims.

What is claimed is:
 1. A method of ensuring accuracy of calculated oddson a computer network, the method comprising: filtering at least onedatabase for live event data; extracting a most recent event from the atleast one database; extracting an event prior to the most recent eventfrom the at least one database, thereby extracting data entries for thetwo most recent events from a live event having a plurality ofsequential events; comparing the extracted data entries for the two mostrecent events from the live event to a plurality of rules from a playrules database; based upon the comparison, determining that theextracted data entries are erroneous; comparing extracted wager marketdata to system rule data from a system rules database; and based uponthe comparison, determining that the extracted wager market data areerroneous.
 2. The method of ensuring accuracy of calculated odds on thecomputer network of claim 1, further comprising: initiating, with a basemodule, a play accuracy module, and a system accuracy module.
 3. Themethod of ensuring accuracy of calculated odds on the computer networkof claim 1, further comprising: regulating the wager market activity byrecognizing a change in live event play data through predeterminedthresholds.
 4. The method of ensuring accuracy of calculated odds on thecomputer network of claim 1, further comprising: regulating the wagermarket activity by recognizing a change in wager profit data throughpredetermined thresholds.
 5. A system for ensuring accuracy ofcalculated odds on a computer network, the system comprising: a playrules database configured to store a plurality of rules; a play accuracymodule configured to compare extracted play data with the plurality ofrules and determine that the extracted play data are erroneous; a systemrules database configured to store system rule data; a system accuracymodule configured to compare extracted wager market data with the systemrule data from the system rules database and determine that theextracted wager market data are erroneous; a base module configured toinitiate the play accuracy module and the system accuracy module; and adevice configured to display a message that either the extracted dataentries are erroneous or the extracted wager market data are erroneous.6. The system for ensuring accuracy of calculated odds on the computernetwork of claim 5, wherein the play accuracy module is furtherconfigured to filter, query, compare, and extract data from the playrules database.
 7. The system for ensuring accuracy of calculated oddson the computer network of claim 6, wherein the play rules database isconfigured to contain rules based on potential system errors data is atleast one of historical, recent, or previous play data.
 8. The systemfor ensuring accuracy of calculated odds on the computer network ofclaim 5, wherein the system accuracy module is further configured tofilter, query, compare, and extract data from the system database. 9.The system for ensuring accuracy of calculated odds on the computernetwork of claim 8, wherein the system rules database is configured tocontain rules based on potential system errors.
 10. The system forensuring accuracy of calculated odds on the computer network of claim 5,wherein the extracted and executed rules are configured to utilize apredetermined threshold.
 11. The system for ensuring accuracy ofcalculated odds on the computer network of claim 10, wherein thepredetermined threshold is configured to be at least one predeterminednumber, time interval, or percentage.
 12. The system for ensuringaccuracy of calculated odds on the computer network of claim 5, whereinthe play rules database is configured to contain rules based onpotential system errors.
 13. The system for ensuring accuracy ofcalculated odds on the computer network of claim 5, wherein the systemrules database is configured to contain rules based on potential systemerrors.
 14. The system for ensuring accuracy of calculated odds on thecomputer network of claim 5, wherein the message is displayed to anadministrator by a notification.
 15. The method of claim 1, wherein bothof the determining steps are performed in real time.
 16. The system ofclaim 5, wherein the play accuracy module and the system accuracy moduleare both configured to perform respective determinations in real time.